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Overjet Caries Assist-Pediatric (OCA-Ped) is a radiological, automated, concurrent-read, computer-assisted detection (CADe) software intended to aid in the detection and segmentation of caries on bitewing and periapical radiographs. The device provides additional information for the clinician to use in their diagnosis of a tooth surface suspected of being carious. The device is not intended as a replacement for a complete dentist's review or their clinical judgment that takes into account other relevant information from the image, patient history, or actual in vivo clinical assessment.

The intended patient population of the device is patients aged 4-11 years old that have primary or permanent teeth (primary or mixed dentition) and are indicated for dental radiographs.

Overjet Caries Assist-Pediatric (OCA-Ped) is a radiological, automated, concurrent-read, computer-assisted detection (CADe) software intended to aid in the detection and segmentation of caries on bitewing and periapical radiographs. The device provides additional information for the dentist to use in their diagnosis of a tooth surface suspected of being carious. The device is not intended as a replacement for a complete dentist's review or their clinical judgment that takes into account other relevant information from the image, patient history, or actual in vivo clinical assessment.

OCA-Ped is a software-only device which operates in three layers: a Network Layer, a Presentation Layer, and a Decision Layer. Images are pulled in from a clinic/dental office, and the Machine Learning model creates predictions in the Decision Laver and results are pushed to the dashboard, which are in the Presentation Layer.

The provided document describes the Overjet Caries Assist-Pediatric (OCA-Ped) device, a computer-assisted detection (CADe) software intended to aid in the detection and segmentation of caries on bitewing and periapical radiographs for patients aged 4-11 years old.

Here's the breakdown of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a separate section with specific numerical thresholds. However, it presents the performance metrics from the MRMC reader study and standalone testing, which can be interpreted as demonstrating the device's acceptable performance.

2. Sample Size Used for the Test Set and Data Provenance

• MRMC Test Set: 636 images, each from a unique patient.
• Standalone Test Set: 1190 bitewing and periapical images.
• Data Provenance: "Images were obtained from male and female patients aged 4-11 years." For the Standalone testing, "images were obtained from male and female patients, from a range of distinctly different geographic regions." The document does not specify if the data was retrospective or prospective, nor does it explicitly mention the country of origin, beyond "US licensed dentists" participating in the MRMC study. Given that "US licensed dentists" participated and "distinctly different geographic regions" are mentioned for standalone, it's implied to be US-centric.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Number of Experts: 3
• Qualifications of Experts: General dentists. No specific experience level (e.g., "10 years of experience") is provided, only "3 general dentists."

4. Adjudication Method for the Test Set

• Adjudication Method: Consensus ground truth established by 3 general dentists. The exact process of reaching consensus (e.g., silent read, discussion, majority vote) is not detailed, but it implies agreement among the three experts.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• Yes, an MRMC comparative effectiveness study was done.
• Effect Size of Improvement with AI Assistance:
  • AUC of wAFROC: Averaged across all readers, there was a 7.5% improvement (95% CI: 0.062, 0.088) in assisted readers compared to unassisted readers.
  • Tooth-level Sensitivity: Averaged across all readers, sensitivity increased by 11.8% (95% CI: 0.102, 0.137) when compared to unassisted readers.
  • Tooth-level Specificity: A slight decrease of -0.011 (95% CI: -0.015, -0.008) between assisted and unassisted readers.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

• Yes, standalone performance testing was done.
  • Tooth-level standalone sensitivity was 83.9% (95% CI: 0.816, 0.860).
  • Tooth-level standalone specificity was 97.5% (95% CI: 0.971, 0.979).
  • Standalone Dice was a mean of 79.0% (95% CI: 0.784, 0.797).

7. The Type of Ground Truth Used

• Ground Truth Type: Expert consensus. Specifically, "consensus reference standard established by 3 general dentists."

8. The Sample Size for the Training Set

• The document does not provide the sample size for the training set. It only describes the test sets used for MRMC and standalone performance evaluation.

9. How the Ground Truth for the Training Set Was Established

• The document does not describe how the ground truth for the training set was established. It only details the ground truth establishment for the test sets.

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